1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
|
{{alias}}( x[, options] )
Performs a chi-square independence test.
For a two-way contingency table `x` (represented as a two-dimensional
`ndarray` or `array` of `arrays`), the null hypothesis that the joint
distribution of the cell counts is the product of the row and column
marginals is tested, i.e. whether the row and column variables are
independent.
The function returns an object containing the test statistic, p-value, and
decision.
Parameters
----------
x: (MatrixLike|Array<Array>)
Two-way table of cell counts.
options: Object (optional)
Options.
options.alpha: number (optional)
Significance level of the hypothesis test. Must be on the interval
[0,1]. Default: 0.05.
options.correct: boolean (optional)
Boolean indicating whether to use Yates' continuity correction when
provided a 2x2 contingency table. Default: true.
Returns
-------
out: Object
Test result object.
out.alpha: number
Significance level.
out.rejected: boolean
Test decision.
out.pValue: number
Test p-value.
out.statistic: number
Test statistic.
out.df: number
Degrees of freedom.
out.expected: ndarray
Expected cell counts.
out.method: string
Test name.
out.print: Function
Function to print formatted output.
Examples
--------
// Provide expected probabilities...
> var x = [ [ 20, 30 ], [ 30, 20 ] ];
> var out = {{alias}}( x )
{ 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }
> out.print()
// Set significance level...
> var opts = { 'alpha': 0.1 };
> out = {{alias}}( x, opts )
{ 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }
> out.print()
// Disable Yates' continuity correction (primarily used with small counts):
> opts = { 'correct': false };
> out = {{alias}}( x, opts )
{...}
See Also
--------
|
